Issue |
EPJ Web Conf.
Volume 247, 2021
PHYSOR2020 – International Conference on Physics of Reactors: Transition to a Scalable Nuclear Future
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Article Number | 04008 | |
Number of page(s) | 8 | |
Section | Monte Carlo Transport | |
DOI | https://doi.org/10.1051/epjconf/202124704008 | |
Published online | 22 February 2021 |
https://doi.org/10.1051/epjconf/202124704008
SUPER-HISTORY METHODS FOR ADJOINT-WEIGHTED TALLIES IN MONTE CARLO TIME EIGENVALUE CALCULATIONS
DEN-Service d’études des réacteurs et de mathématiques appliquées (SERMA), CEA, Université Paris-Saclay, F-91191, Gif-sur-Yvette, France
alexis.jinaphanh@cea.fr
andrea.zoia@cea.fr
Published online: 22 February 2021
Time eigenvalues emerge in several key applications related to neutron transport problems, including reactor start-up and reactivity measurements. In this context, experimental validation and uncertainty quantification would demand to assess the variation of the dominant time eigenvalue in response to a variation of nuclear data. Recently, we proposed the use of a Generalized Iterated Fission Probability method (G-IFP) to compute adjoint-weighted tallies, such as kinetic parameters, perturbations and sensitivity coefficients, for Monte Carlo time (or alpha) eigenvalue calculations. With the massive use of parallel Monte Carlo calculations, it would be therefore useful to trade the memory burden of the G-IFP method (which is comparable to that of the standard IFP method for k-eigenvalue problems) for computation time and to rely on history-based schemes for such adjoint-weighted tallies. For this purpose, we investigate the use of the super-history method as applied to estimating adjoint-weighted tallies within the α-k power iteration, based on previous work on k-eigenvalue problems. Verification of the algorithms is performed on some simple preliminary tests where analytic solutions exist. In addition, the performances of the proposed method are assessed by comparing the super-history and the G-IFP methods for the same sets of benchmark problems.
Key words: Time-eigenvalue / Perturbations / Sensitivity coefficients / Super-history
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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